文章
共发表SCI论文170余篇，其中以第一作者或通讯作者在Radiology（4篇）、JACC Cardiovascular Imaging、 Neurology、JNNP等国际知名期刊上发表SCI论文140余篇， JCR Q1区70余篇。
部分代表性SCI论文
1. Gong X, Wang X, Wang L, Zeng X, Tang S, Cheng Y, Yu T, Huang Y, Cao Y, Chen H, Jiang F, Liu S, Li L, Yin T, Zhang J. Comparing Multi-b-Value Diffusion MRI Models for Predicting Pathologic Complete Response to Neoadjuvant Chemotherapy in Breast Cancer. Radiology. 2025;316(1):e242969. doi: 10.1148/radiol.242969. PubMed PMID: 40693938.
2. Huang Y, Wang X, Cao Y, Lan X, Hu X, Mou F, Chen H, Gong X, Li L, Tang S, Wang L, Zhang J. Nomogram for Predicting Neoadjuvant Chemotherapy Response in Breast Cancer Using MRI-based Intratumoral Heterogeneity Quantification. Radiology. 2025;315(1):e241805. doi: 10.1148/radiol.241805.
3. Long L, Liu M, Deng X, Jin J, Cao M, Zhang J, Tao J, Shen H, Wang X, Liu D, Zhang J. Tumor Stiffness Measurement at Multifrequency MR Elastography to Predict Lymphovascular Space Invasion in Endometrial Cancer. Radiology. 2024;311(3):e232242. doi: 10.1148/radiol.232242. PubMed PMID: 38832881.
4. Wang X, Ba R, Huang Y, Cao Y, Chen H, Xu H, Shen H, Liu D, Huang H, Yin T, Wu D, Zhang J. Time-Dependent Diffusion MRI Helps Predict Molecular Subtypes and Treatment Response to Neoadjuvant Chemotherapy in Breast Cancer. Radiology. 2024;313(1):e240288. doi: 10.1148/radiol.240288. PubMed PMID: 39436292.
5. Huang Y, Gong H, Hu W, Ren H, Cao Y, Lan X, Chen H, Wang L, Wang X, Zhang J. Fractal analysis of longitudinal MRI for predicting response to neoadjuvant chemotherapy in breast cancer. npj Precision Oncology. 2025. doi: 10.1038/s41698-025-01220-0.
6. Zhang J, Ji B, Hu J, Zhou C, Li L, Li Z, Huang X, Hu X. Aberrant interhemispheric homotopic functional and structural connectivity in amyotrophic lateral sclerosis. J Neurol Neurosurg Psychiatry. 2017;88(5):369-70. doi: 10.1136/jnnp-2016-314567. PubMed PMID: 27913627.
7. Tang X, Zhang Y, Liu D, Hu Y, Jiang L, Zhang J. Association of Gyrification Pattern, White Matter Changes, and Phenotypic Profile in Patients With Parkinson Disease. Neurology. 2021;96(19):e2387. doi: 10.1212/WNL.0000000000011894.
8. Shen H, Lian Y, Yin J, Zhu M, Yang C, Tu C, Peng Y, Li X, Zhang J. Cardiovascular Risk Stratification by Automatic Coronary Artery Calcium Scoring on Pretreatment Chest Computed Tomography in Diffuse Large B-Cell Lymphoma Receiving Anthracycline-Based Chemotherapy: A Multicenter Study. Circulation: Cardiovascular Imaging. 2023. doi: 10.1161/circimaging.122.014829.
9. Tu C, Shen H, Li X, Wang X, Miao Z, Deng W, Liu R, Lan X, Chen H, Zhang J. Longitudinal Evaluation of Coronary Arteries and Myocardium in Breast Cancer Using Coronary Computed Tomographic Angiography. JACC Cardiovasc Imaging. 2024. Epub 20240627. doi: 10.1016/j.jcmg.2024.05.017. PubMed PMID: 39001732.
10. Shen H, Xu Q, Tu C, Peng Y, Xie Y, Miao Z, Yang R, Zhang J. Left ventricular trabecular complexity for risk stratification of cancer therapy-related cardiac dysfunction in breast cancer. MedComm (2020). 2025;6(1):e70004. Epub 20250102. doi: 10.1002/mco2.70004. PubMed PMID: 39760113; PMCID: PMC11695210.
11. Chen H, Wang X, Huang Y, Cao Y, Cao M, Hu X, Mou F, Gong X, Tang S, Wang L, Li L, Yu T, Cheng Y, Zhang J. Nomograms Integrating MRI-derived Apparent Diffusion Coefficient and Clinicopathologic Features for Prediction of Axillary Lymph Node Metastasis in Breast Cancer. Radiology: Imaging Cancer. 2025;7(2):e240202. doi: 10.1148/rycan.240202. PubMed PMID: 40116606.
12. Wang X, Hu X, Wang C, Yang H, Hu Y, Lan X, Huang Y, Cao Y, Yan L, Zhang F, Yu Y, Zhang J. Automatic Segmentation and Molecular Subtype Classification of Breast Cancer Using an MRI-based Deep Learning Framework. Radiology: Imaging Cancer. 2025;7(3):e240184. doi: 10.1148/rycan.240184. PubMed PMID: 40249269.
13. Shen H, Yin J, Niu R, Lian Y, Huang Y, Tu C, Liu D, Wang X, Lan X, Yuan X, Zhang J. MRI-based radiomics to compare the survival benefit of induction chemotherapy plus concurrent chemoradiotherapy versus concurrent chemoradiotherapy plus adjuvant chemotherapy in locoregionally advanced nasopharyngeal carcinoma: A multicenter study. Radiotherapy and Oncology. 2022;171:107-13. doi: https://doi.org/10.1016/j.radonc.2022.04.017.
14. Xie Y, Shen H, Xu Q, Tu C, Yang R, Liu T, Tang H, Miao Z, Zhang J. Evaluating coronary arteries and predicting MACEs using CCTA in lung cancer patients receiving chemotherapy or chemoradiotherapy. Radiotherapy and Oncology. 2024;200. doi: 10.1016/j.radonc.2024.110498.
15. Xu Q, Shen H, Wen L, Tu C, Deng W, Liu R, Zhang F, Zheng D, Zhang J. Development and validation of A CCTA-based risk prediction model for major adverse cardiovascular events in esophageal cancer patients receiving radiotherapy. Radiotherapy and Oncology. 2026;216:111364. doi: https://doi.org/10.1016/j.radonc.2026.111364.
16. Luo Y, Liu L, Liu D, Shen H, Wang X, Fan C, Zeng Z, Zhang J, Tan Y, Zhang X, Wu J, Zhang J. Extracellular volume fraction determined by equilibrium contrast-enhanced CT for the prediction of the pathological complete response to neoadjuvant chemoradiotherapy for locally advanced rectal cancer. Eur Radiol. 2023;33(6):4042-51. Epub 2022/12/04. doi: 10.1007/s00330-022-09307-z. PubMed PMID: 36462046.
17. Peng Y, Shen H, Tang H, Huang Y, Lan X, Luo X, Zhang X, Zhang J. Nomogram based on CT-derived extracellular volume for the prediction of post-hepatectomy liver failure in patients with resectable hepatocellular carcinoma. Eur Radiol. 2022;32(12):8529-39. Epub 20220609. doi: 10.1007/s00330-022-08917-x. PubMed PMID: 35678856.
18. Chen L, Su Y, Huang Y, Tao J, Huang X, Li K, Liu D, Zhang J. Predicting lymphovascular invasion in stage IA lung adenocarcinoma: a CT-based classification and regression tree model. European Radiology. 2025. doi: 10.1007/s00330-025-11593-2.
19. Liu Y, Cheng F, Wang L, Du L, Shen H, Wang X, Zeng Z, Liu D, Tao J, Wu J, Zhang J. Quantitative parameters derived from dual-energy computed tomography for the preoperative prediction of early recurrence in patients with esophageal squamous cell carcinoma. European Radiology. 2023. doi: 10.1007/s00330-023-09818-3.
20. Ren H, Huang J, Liu D, Huang Y, Ren X, Zhang J, Tan Y, Yu H, Zheng J, Tang L, Wang Y, Zhang J. Evaluation of induction chemotherapy response using multiphasic dual-energy CT in nasopharyngeal carcinoma. European Radiology. 2025. doi: 10.1007/s00330-025-11512-5.
21. Shi J, Huang H, Xu S, Du L, Zeng X, Cao Y, Liu D, Wang X, Zhang J. XGBoost-based multiparameters from dual-energy computed tomography for the differentiation of multiple myeloma of the spine from vertebral osteolytic metastases. European Radiology. 2023. doi: 10.1007/s00330-023-09404-7.
22. Wang X, Tan Y, Liu D, Shen H, Deng Y, Tan Y, Wang L, Zhang Y, Ma X, Zeng X, Zhang J. Chemotherapy-associated steatohepatitis was concomitant with epicardial adipose tissue volume increasing in breast cancer patients who received neoadjuvant chemotherapy. European Radiology. 2022;32(7):4898-908. doi: 10.1007/s00330-022-08581-1.
23. Cao Y, Wang X, Li L, Shi J, Zeng X, Huang Y, Chen H, Jiang F, Yin T, Nickel D, Zhang J. Early prediction of pathologic complete response of breast cancer after neoadjuvant chemotherapy using longitudinal ultrafast dynamic contrast-enhanced MRI. Diagnostic and Interventional Imaging. 2023;104(12):605-14. doi: 10.1016/j.diii.2023.07.003.
24. Cao Y, Wang X, Shi J, Zeng X, Du L, Li Q, Nickel D, Zhou X, Zhang J. Multiple parameters from ultrafast dynamic contrast-enhanced magnetic resonance imaging to discriminate between benign and malignant breast lesions: Comparison with apparent diffusion coefficient. Diagnostic and Interventional Imaging. 2023;104(6):275-83. doi: https://doi.org/10.1016/j.diii.2023.01.006.
25. Deng X, Liu M, Zhou Q, Zhao X, Li M, Zhang J, Shen H, Lan X, Zhang X, Zhang J. Predicting treatment response to concurrent chemoradiotherapy in squamous cell carcinoma of the cervix using amide proton transfer imaging and intravoxel incoherent motion imaging. Diagnostic and Interventional Imaging. 2022;103(12):618-24. doi: https://doi.org/10.1016/j.diii.2022.09.001.
26. Huang Y, Wang X, Cao Y, Li M, Li L, Chen H, Tang S, Lan X, Jiang F, Zhang J. Multiparametric MRI model to predict molecular subtypes of breast cancer using Shapley additive explanations interpretability analysis. Diagnostic and Interventional Imaging. 2024;105(5):191-205. doi: https://doi.org/10.1016/j.diii.2024.01.004.
27. Long L, Sun J, Jiang L, Hu Y, Li L, Tan Y, Cao M, Lan X, Zhang J. MRI-based traditional radiomics and computer-vision nomogram for predicting lymphovascular space invasion in endometrial carcinoma. Diagnostic and Interventional Imaging. 2021. doi: https://doi.org/10.1016/j.diii.2021.02.008.
28. Tao J, Liang C, Yin K, Fang J, Chen B, Wang Z, Lan X, Zhang J. 3D convolutional neural network model from contrast-enhanced CT to predict spread through air spaces in non-small cell lung cancer. Diagnostic and Interventional Imaging. 2022;103(11):535-44. doi: https://doi.org/10.1016/j.diii.2022.06.002.
29. Huang Y, Cao Y, Hu X, Lan X, Chen H, Tang S, Li L, Cheng Y, Gong X, Wang W, Jiang F, Yin T, Wang X, Zhang J. Early Identification of Pathologic Complete Response to Neoadjuvant Chemotherapy Using Multiphase DCE-MRI by Siamese Network in Breast Cancer: A Longitudinal Multicenter Study. J Magn Reson Imaging. 2024;60(4):1325-37. Epub 20231218. doi: 10.1002/jmri.29188. PubMed PMID: 38109316.
30. Ren H, Shi D, Huang J, Yu H, Yin T, Liu D, Zhang J. Differentiating Benign Thyroid Nodules and Papillary Thyroid Carcinoma Using Time-Dependent Diffusion MRI: A Feasibility Study. J Magn Reson Imaging. 2025. Epub 20250820. doi: 10.1002/jmri.70065. PubMed PMID: 40836573.
31. Wang X, Huang Y, Cao Y, Chen H, Gong X, Lan X, Zhang J, Ye Z. Time-Dependent Diffusion MRI-Based Microstructural Mapping for Characterizing HER2-Zero, -Low, -Ultra-Low, and -Positive Breast Cancer. J Magn Reson Imaging. 2025. Epub 20250820. doi: 10.1002/jmri.70074. PubMed PMID: 40831438.
32. Wang X, Liu D, Jiang S, Zeng X, Li L, Yu T, Zhang J. Subjective and Objective Assessment of Monoenergetic and Polyenergetic Images Acquired by Dual-Energy CT in Breast Cancer. Korean Journal of Radiology. 2021;22. doi: 10.3348/kjr.2020.0310.
项目
主持国家及省部级课题10余项，包括国家自然科学基金面上项目2项、省部级重点项目2项。
1. 重庆大学，中央高校基本科研业务费“医工融合项目”，基于肺部CT深度流形对齐的NSCLC脑转移预测模型的构建和验证，2019.9- 2021.8，30万元，已结题, 主持
2. 重庆市卫生健康委员会、重庆市科学技术局，重庆市科卫联合医学科研项目重点项目，基于深度迁移学习的肺部CT鳞、腺癌分类及基因突变预测，2019.9-2022.8，20万元，已结题，主持
3. 国家自然科学基金委员会，面上项目，基于多模态磁共振成像探索癌痛与抑郁交互作用的神经机制研究，2021.01-2024.12, 55万元，已结题，主持
4. 影像科重庆市临床重点专科建设经费，110万元，在研，主持
5. 重庆市科学技术局，面上项目，基于多模态MRI探讨阿片诱导癌痛病人痛觉过敏的丘脑环路机制研究，2021.10-2024.9，10万元，提前结题，主持
6. 2021年中华国际医学交流基金会SKY影像科研基金前沿项目，影像组学跨模态跨尺度联合病理组学精准预测局部进展期乳腺癌新辅助治疗疗效的研究，2022.01.01 – 2023.12.31, 30万元，已结题，主持
7. 重庆市卫生健康委员会、重庆市科学技术局，重庆市科卫联合医学科研项目重点项目，非小细胞肺癌多模态影像精准诊断系统研究与应用，2023.01-2025.12，20万元，已结题，主持
8. 重庆大学附属肿瘤医院科研能力提升专项项目，基于MRI探讨HER2阳性乳腺癌新辅助治疗耐药及心脏毒性的作用机制研究，2023.08.01-2026.07.31, 50万元，在研，主持
9. 国家自然科学基金委员会，面上项目，基于多模态MRI探讨突显网络受损介导自发性癌性爆发痛的机制及TMS干预研究，2024.01-2027.12，50万元，在研，主持
10. 重庆市科学技术局，面上项目，基于多参数MRI探索脑血管损伤介导化疗相关认知障碍机制的研究，2024.07-2027.06，10万元，在研，主持
获奖
2013年获得重庆市科技进步奖二等奖一项
2019年入选重庆市中青年医学高端人才
2022年入选重庆大学附属肿瘤医院高端人才
2024年入选重庆市学术技术带头人、重庆市医学领军人才
2025年入选爱思唯尔“全球前2%顶尖科学家榜单”
